Skill UI

OSS-Fuzz gives open-source teams free distributed infrastructure for continuous fuzz testing, letting you build Docker images, compile sanitizing fuzzers, run harnesses, and review coverage/bugs through the helper.py CLI instead of hosting your own servers.

Helps developers systematically optimize web performance by measuring key metrics, reducing bundle size, deferring scripts, optimizing images and fonts, and tuning caching and CSS for faster Time to Interactive and better Lighthouse scores.

Scans container images and running containers using Trivy and Snyk to identify vulnerabilities, rank them by severity, and return remediation guidance whenever users ask for a security assessment before or after deployment.

This guide establishes a fast, reproducible local development workflow for GPU workloads using Vast.ai. It covers key practices such as testing Docker images locally (in CPU mode), mocking external APIs like Vast.ai, and implementing robust unit and integration tests. This is essential for minimizing cloud GPU costs and accelerating the iteration cycle for complex AI/ML projects.

This deep dive guides users through migrating complex GPU workloads, such as deep learning training pipelines, from major hyperscalers (AWS, GCP, Azure) or other cloud platforms to Vast.ai. It covers critical steps including cost comparison analysis, adapting Docker images for new environments, securely handling cloud credentials via environment variables, and implementing robust validation and rollback procedures to ensure a smooth transition.

Comprehensive guide for upgrading the Vast.ai CLI and Python SDK. This skill helps users manage API version migrations, detect breaking changes, and update associated Docker images (e.g., CUDA versions). It ensures continuous compatibility when working with cloud GPU computing resources.

This skill leverages AI to analyze your application and automatically generate highly optimized Dockerfiles. It incorporates industry best practices like multi-stage builds, minimal base images, and robust security configurations. Use it when containerizing applications or needing to optimize existing Docker configurations for production deployment and efficient orchestration.

Generate premium images, videos, and audio straight from the terminal using muapi.ai’s schema-driven workflows and 100+ models such as Flux, Midjourney, Kling, Veo, and Suno.

MarkItDown converts PDFs, DOCX, PPTX, XLSX, HTML, JSON, XML, archives, YouTube links, images via OCR, and audio via transcription into clean Markdown, providing token-efficient text ready for LLMs and documentation workflows.

Manage microscopy data with the OMERO Python API: access projects/datasets/images, retrieve and analyze pixel data, handle ROIs and annotations, store results in tables, and automate batch workflows for high-content screening.

Apify Actorization is a process that transforms existing, standalone software or scripts (like CLI tools) into standardized, reusable serverless applications called Actors. Actors are packaged as Docker images, accepting structured JSON inputs and producing structured JSON outputs. This skill guides developers on migrating projects to the Apify platform, ensuring compatibility, and enabling scalable, event-driven data processing pipelines.

Creates a Next.js page that renders App Store screenshots as marketing ads, exports Apple‑sized images via html-to-image, and supports branded styling, locale tabs, and reusable theme presets for iOS listings.